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Edge computing has emerged as a pivotal technology, offering significant advantages such as low latency, enhanced data security, and reduced reliance on centralized cloud infrastructure. These benefits are crucial for applications requiring…

FPGA accelerators for lightweight neural convolutional networks (LWCNNs) have recently attracted significant attention. Most existing LWCNN accelerators focus on single-Computing-Engine (CE) architecture with local optimization. However,…

The PANDA experiment is one of the four large experiments being built at FAIR in Darmstadt. It will use a cooled antiproton beam on a fixed target within the momentum range of 1.5 to 15 GeV/c to address questions of strong QCD, where the…

The Daya Bay Reactor Neutrino Experiment started running on September 23, 2011. The offline computing environment, consisting of 11 servers at Daya Bay, was built to process onsite data. With current computing ability, onsite data…

Synaptic delay has attracted significant attention in neural network dynamics for integrating and processing complex spatiotemporal information. This paper introduces a high-throughput Spiking Neural Network (SNN) processor that supports…

Deep Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in a wide range of applications. However, deeper CNN models, which are usually computation consuming, are widely required for complex Artificial…

While embedded FPGAs are attractive platforms for DNN acceleration on edge-devices due to their low latency and high energy efficiency, the scarcity of resources of edge-scale FPGA devices also makes it challenging for DNN deployment. In…

This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, to perform high-throughput inference by exploiting the computation time-accuracy trade-off. Without the need for retraining, a…

Point cloud registration serves as a basis for vision and robotic applications including 3D reconstruction and mapping. Despite significant improvements on the quality of results, recent deep learning approaches are computationally…

We present a full-stack optimization framework for accelerating inference of CNNs (Convolutional Neural Networks) and validate the approach with field-programmable gate arrays (FPGA) implementations. By jointly optimizing CNN models,…

Convolutional neural networks (CNNs) with large kernels, drawing inspiration from the key operations of vision transformers (ViTs), have demonstrated impressive performance in various vision-based applications. To address the issue of…

Performance of distributed data center applications can be improved through use of FPGA-based SmartNICs, which provide additional functionality and enable higher bandwidth communication. Until lately, however, the lack of a simple approach…

Edge computing solutions that enable the extraction of high-level information from a variety of sensors is in increasingly high demand. This is due to the increasing number of smart devices that require sensory processing for their…

KLOE, a new state of the art detector recently commissioned for physics operation at DAFNE, has many innovative interesting features, especially in the DAQ and Trigger areas. Custom electronics assert a trigger in a 2 microseconds decision…

LiDAR sensors have been widely used in many autonomous vehicle modalities, such as perception, mapping, and localization. This paper presents an FPGA-based deep learning platform for real-time point cloud processing targeted on autonomous…

In this paper, we present a complete Data Acquisition System (DAQ) together with the readout mechanisms for the J-PET tomography scanner. In general detector readout chain is constructed out of Front-End Electronics (FEE), measurement…

DUNE will be the world's largest neutrino experiment due to take data in 2025. Here is described the data acquisition (DAQ) system for one of its prototypes - ProtoDUNE-SP due to take data in Q4 of 2018. ProtoDUNE-SP also breaks records as…

Deep neural networks (DNNs) are used by different applications that are executed on a range of computer architectures, from IoT devices to supercomputers. The footprint of these networks is huge as well as their computational and…

During the third long shutdown of the CERN Large Hadron Collider, the CMS Detector will undergo a major upgrade to prepare for Phase-2 of the CMS physics program, starting around 2026. The upgraded CMS detector will be read out at an…

The Jinping Neutrino Experiment(JNE), conducted within the China Jinping Underground Laboratory, aims to detect and analyze of solar neutrinos, geo-neutrinos, and supernova neutrinos. A one-ton prototype will soon be in commision with an…